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The model for end-stage liver disease (MELD) score, which can reflect liver and renal function, is associated with poor prognosis. However, the prognostic performance of the modified MELD score in patients undergoing elective percutaneous coronary intervention (PCI) has not been fully evaluated and compared. This study retrospectively enrolled 5324 patients. During a median follow-up of 2.85 years, 412 patients died. Time-dependent receiver operating characteristic curves at 3 years indicated that the MELD including albumin (MELD-Albumin) score had the highest prognostic performance (AUC = .721) than the MELD score (AUC = .630), the MELD excluding the international normalized ratio (MELD-XI) score (AUC = .606), and the MELD including sodium (MELD-Na) score (AUC = .656) (all < .001). The MELD-Albumin score, the MELD score, and the MELD-Na score were independent predictors of long-term mortality; however, the MELD-XI score was not when treated as a categorical variable ( = .254). Adding the MELD-Albumin score to the model of clinical risk factors could improve the prognostic performance. For the subgroup analysis, the association between the MELD-Albumin score and long-term mortality was more pronounced in patients ≤75 years (interaction value = .005). The MELD-Albumin score showed the strongest prognostic performance than the other versions of the MELD score in patients undergoing elective PCI.
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http://dx.doi.org/10.1177/00033197221098288 | DOI Listing |
Ren Fail
December 2025
Department of Critical Care Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, China.
This study aimed to develop a predictive model and construct a graded nomogram to estimate the risk of severe acute kidney injury (AKI) in patients without preexisting kidney dysfunction undergoing liver transplantation (LT). Patients undergoing LT between January 2022 and June 2023 were prospectively screened. Severe AKI was defined as Kidney Disease: Improving Global Outcomes stage 3.
View Article and Find Full Text PDFArq Gastroenterol
September 2025
Alimentary Tract Research Center, Clinical Sciences Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Background: Acute upper gastrointestinal bleeding (AUGIB) is a critical medical emergency and is a common cause of illness and death in individuals with liver cirrhosis.
Objective: The point of this study was to check how well the albumin-to-bilirubin ratio (ALBI) and model for end-stage liver disease (MELD) scores could predict how these patients would do in the future.
Methods: The Imam Khomeini Hospital gastroenterology department conducted a retrospective examination.
Hepatology
September 2025
Department of Gastroenterology and Hepatology, UT Southwestern, Dallas, TX.
Background: The clinical course and outcomes of alcohol-associated hepatitis (AH) remain poorly understood. Major adverse liver outcomes (MALO) do not capture the added risk of return to drinking (RTD). We examined the natural history of AH and developed a composite endpoint using a contemporary observational cohort of AH.
View Article and Find Full Text PDFLiver Int
October 2025
Hannover Medical School, Department of Diagnostic and Interventional Radiology, Hannover, Germany.
Background And Aims: We aimed to ascertain the prevalence of sarcopenia in patients with primary sclerosing cholangitis (PSC) and to assess the prognostic value as a biomarker for disease outcome.
Methods: We collected data from 224 patients (148 male, 76 female; mean age 41 years) from January 2002 to December 2021, with a confirmed diagnosis of PSC who underwent magnetic resonance imaging (MRI). Muscle mass was quantified at the level of the third lumbar vertebra by measurement of psoas muscle thickness (PMT) and total psoas muscle area (PMA).
PLoS One
September 2025
School of Software, Hunan College of Information, Chang sha, Hunan Province, China.
This research has proposed a new Emotion Recognition in Conversation (ERC) model known as Hierarchical Graph Learning for Emotion Recognition (HGLER), built to go beyond the existing approaches that find it difficult to request long-distance context and interaction across different data types. Rather than simply mixing different kinds of information, as is the case with traditional methods, HGLER uses a 2-part graph technique whereby conversations are represented in a 2-fold manner: one aimed at illustrating how various parts of the conversation relate and another for enhancing learning from various types of data. This dual-graph system can represent multimodal data value for value by exploiting the benefits of each type of data yet tracking their interactions.
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